Parametric generalized singular perturbation approximation for model order reduction

2000 ◽  
Vol 45 (2) ◽  
pp. 339-343 ◽  
Author(s):  
G. Muscato
Keyword(s):  
Singular Perturbation ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Model Order ◽  
Perturbation Approximation

Singular perturbation approximation for linear systems with Lévy noise

2018 ◽  
Vol 18 (04) ◽  
pp. 1850033 ◽  
Author(s):  
Martin Redmann ◽  
Peter Benner
Keyword(s):  
Singular Perturbation ◽  
Linear Systems ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Reduction Technique ◽  
Lévy Noise ◽  
Model Order ◽  
Linear Evolution Equation ◽  
Levy Noise ◽  
Perturbation Approximation

To solve a stochastic linear evolution equation numerically, finite dimensional approximations are commonly used. For a good approximation, one might end up with a sequence of ordinary stochastic linear equations of high order. To reduce the high dimension for practical computations, we consider the singular perturbation approximation as a model order reduction technique in this paper. This approach is well-known from deterministic control theory and here we generalize it for controlled linear systems with Lévy noise. Additionally, we discuss properties of the reduced order model, provide an error bound, and give some examples to demonstrate the quality of this model order reduction technique.

A Singular Perturbation Model Order Reduction Method for a Specially Structured Model

2004 ◽  
Vol 10 (2) ◽  
pp. 309-316
Author(s):  
Sedig S Agili ◽  
Omid Ansary ◽  
Faramarz Mossayebi
Keyword(s):  
Singular Perturbation ◽  
Model Order Reduction ◽  
Linear Time ◽  
Computational Cost ◽  
Order Reduction ◽  
Reduction Technique ◽  
Algebraic Riccati Equation ◽  
Model Order ◽  
Analysis And Design ◽  
Perturbation Model

In this paper we consider a model order reduction technique in the context of a special descriptor representation of linear time-invariant continuous-time systems. Specifically, we present a unique form of singular perturbation model order reduction technique for such a representation. It is shown that this technique leads to a reduced-order model with an upper triangular system matrix. This method also results in one algebraic Riccati equation instead of two, which are generally required for singular perturbation model order reduction techniques. The foregoing structure enables the analysis and design of large dimensional systems with less computational cost and errors in comparison to the existing methods. An example is also given to illustrate the application of the proposed method.

THE NEW ALGORITHM OF SOLVING HARMONIC BALANCE EQUATIONS

2019 ◽  
Author(s):  
Vladimir Lantsov ◽  
A. Papulina
Keyword(s):  
Harmonic Balance ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Balance Equations ◽  
Model Order ◽  
Cad Systems ◽  
Computational Costs ◽  
Reduction Methods ◽  
Model Equations

The new algorithm of solving harmonic balance equations which used in electronic CAD systems is presented. The new algorithm is based on implementation to harmonic balance equations the ideas of model order reduction methods. This algorithm allows significantly reduce the size of memory for storing of model equations and reduce of computational costs.

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